Niraj Prasad Koirala

This paper investigates the impact of food price inflation on gender inequality based on a panel dataset of 130 developing countries from 1990 to 2022. Applying the dynamic panel estimation techniques, including the system generalized method of moments (system GMM) and fixed-effects panel instrumental variable (panel IV) approaches, we find that food inflation significantly increases gender inequality, especially in areas such as education, labor market, health, and food security. The inflationary impact on gender inequality is strongest for staple food items like potatoes, wheat, and eggs, which are most fundamental to household consumption and care work activities typically performed by women. Since gender inequality, defined as the unequal distribution of resources, opportunities, and rights between men and women across key social and economic dimensions, is shaped by structural, cultural, and institutional factors, we further conduct heterogeneity analyses. The results reveal that poorer countries and African region are more exposed to the gendered effect of food price inflation, whereas countries with stronger institutional frameworks, such as those in OECD and Latin America, have a buffering influence. Synthetic control studies further show that the 2007–2008 food crisis had a more profound and long-lasting effect on gender inequality compared to the 2021–2022 food crisis, which was mainly driven by labor market differentials in female participation and wage earnings. These consistent results call for gender-responsive policy interventions to mitigate the adverse effects of food price inflation on gender inequality and shield women from escalating burdens induced by food inflation.

The credit constraint, an example of an incomplete credit market, provides an incentive to intensify the extensive and intensive margins related to labor force participation and work hours, respectively. This study uses the cross-section data from the Survey of Consumer Finance (SCF) and analyzes the impact of credit constraints on labor supply decisions, time to search for employment, and work hours. The empirical findings using the IV-probit and 2SLS models suggest that credit constraints and their various measures encourage households to increase both labor force participation and work hours to offset the negative impact of financial constraints. The intensity of working hours increases when we introduce both the alternate form of credit constraint and various age bands. Credit-constrained individuals effectively search for jobs and are most likely to accept employment in a short period, but their job search process takes more time than non-constrained individuals.

This study explores how financial development and openness influence the effectiveness of fiscal and monetary policies. An analysis of data from about 100 countries between 1980 and 2018 reveals that both financial openness and development weaken the impact of monetary and fiscal policies. Our results further show that financial development in a country diminishes policy effectiveness depending on the country’s level of financial development; specifically, the more developed a country, the less effective the policies would be. Additionally, through a detailed examination employing a dynamic panel GMM approach, the study investigates the global repercussions of economic downturns in the US and how financial maturity shapes policy effectiveness during these times. We also discuss some policy implications that show that the positive impacts of monetary policy on output growth are lessened during crisis periods, and policymakers should act accordingly.

In this paper, we assess the impacts of the five most recent pandemics on the volatility of stock prices across forty-nine sectors of the economy in the United States. These five most recent pandemics are the 1957–1958 Asian flu, the 1977 Russian flu, SARS-CoV-1, swine flu and COVID-19. Applying the GJR-GARCH model, we find that pandemics other than COVID-19 have heterogeneous impacts on the volatility of stock returns. The results of our analysis indicate that COVID-19 has increased the volatility of stock returns in all sectors. Similarly, stocks in more than seventy percent of sectors in our study declined during the ongoing pandemic, perhaps reflecting the severity of the pandemic. In addition, our results on sectors such as healthcare and natural gas diverge from other literature. The mixed results on SARS-CoV-1 are partially explained by the fact it emerged at a time when stock valuations were particularly pessimistic. In the case of Russian flu, it was relatively short-lived and limited in spread relative to other pandemics in our study.

In this paper, we study the effects of uncertainty shocks in a quantitative framework where firms in the corporate sector are constrained by credit. Specifically, we formulate borrowing constraints as a nested function that features both earnings and capital as alternative instruments for assessing credit worthiness, in line with recent trends in corporate finance. We find that the quantitative framework that incorporates only one instrument (capital or earnings) in the borrowing constraint falls short in matching the business cycle properties of the US economy in terms of the behavior of output, inflation, and the price markup which are an essential part of the literature on uncertainty shocks. Rather, a hybrid formulation of the borrowing constraint which accounts for both capital and earnings helps us bring the results in the quantitative model closer to the data.